{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "75b4dda2-d02a-4594-ab0c-7e441f2684f5",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "997a8b73-eeb0-443b-aec3-426183a7583d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = np.array([5,5])\n",
    "y = np.array([2,2])\n",
    "np.dot(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b0a2c654-3a43-493d-902f-2a2c4d09f5c8",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "x = np.array([[5,5]])\n",
    "y = np.array([[2,2]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "c31c3828-fde0-4978-b5c6-824e16383bbb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[10, 10]])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.multiply(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "0354b3d6-cc3e-44ec-8159-2d372e2a1793",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[10, 10]])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x * y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "23e08123-e862-4442-87b5-c9c0081f7132",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[10, 10],\n",
       "       [10, 10]])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.matmul(x.T, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ad8eb12b-e528-40c4-8448-3ce4e25dd9bf",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 1, 1],\n",
       "       [4, 5, 6]])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = np.array([1,1,1])\n",
    "y = np.array([[1,1,1],[4,5,6]])\n",
    "x*y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "65dd54f7-2917-4521-905e-f2c545db3c8f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True,  True,  True])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = np.array([1,1,1])\n",
    "y = np.array([1,1,1])\n",
    "x == y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "77d841a6-5dca-48a1-b095-e6e66e6993f5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
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   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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